RT Journal Article
SR Electronic
T1 Reservoir-property inversion â€” A method for quantitative interpretation of seismic-inversion results
JF The Leading Edge
FD Society of Exploration Geophysicists
SP 445a1
OP 445a6
DO 10.1190/tle36050445a1.1
VO 36
IS 5
A1 Zhao, Zhiyong
A1 Nicholson, Frank
A1 Bourne, John
A1 Hilterman, Fred
YR 2017
UL http://tle.geoscienceworld.org/content/36/5/445a1.abstract
AB With improved seismic data quality, prestack inversion has become a routine process for quantitative seismic interpretation. However, direct products from traditional seismic inversion usually are P-impedance (PI), S-impedance (SI), and, in some cases, density. These elastic properties are only an indirect description of subsurface geology. A bridge must be established from inverted PI, SI, and density to more understandable reservoir properties: lithology, porosity, and water saturation. Reservoir-property inversion is a model-based inversion process to transform PI, SI, and density to lithology, porosity, and water saturation. The inversion is performed in two steps: (1) well-log inversion on log data to estimate optimal elastic properties of rock-grain constituents and (2) reservoir-property inversion to estimate reservoir properties from PI, SI, and density. The underlying rock-physics models are the same for both inversions including massâ€“balance equation, Gassmann equation, Voigt-Reuss-Hill average, and Krief's relationship, or, optionally, the Xu-White velocity model. The solution of the inversion is considered as optimal in terms of minimum misfit of PI, SI, and density modeled with inverted reservoir properties compared to the input PI, SI, and density. The inversion results honor all the interrelationships between various elastic properties, reservoir properties, and rock-grain properties. A limitation of the proposed inversion includes a requirement for lithology with only two solid constituents, such as sand mixed with shale. It also requires a density volume as one of the primary input data for the inversion. Due to the inversion's sensitivity to fluid contents, estimated water saturation in many cases may not be reliable. This paper presents the inversion methodology and the inversion results from a set of modeled data as well as a real case study to demonstrate the inversion's capability.